Edge adaptive and energy preserving volume upscaling for high quality volume rendering
Andrea Giachetti, José Antonio Iglesias Guitián, and Enrico Gobbetti
November 2010
Abstract
We describe an edge-directed optimization-based method for volumetric data supersampling. The method is based on voxel splitting and iterative refinement performed with a greedy optimization driven by the smoothing of second order gray level derivatives and the assumption that the average gray level in the original voxels region cannot change. Due to these assumptions, the method, which is the 3D extension of a recently proposed technique, is particularly suitable for upscaling medical imaging data creating physically reasonable voxel values and overcoming the so-called partial volume effect. The good quality of the results obtained is demonstrated through experimental tests. Furthermore, we show how offline 3D upscaling of volumes can be coupled with recent techniques to perform high quality volume rendering of large datasets, obtaining a better inspection of medical volumetric data.
Reference and download information
Andrea Giachetti, José Antonio Iglesias Guitián, and Enrico Gobbetti. Edge adaptive and energy preserving volume upscaling for high quality volume rendering. In Eurographics Italian Chapter Conference. Pages 17-23. Eurographics Association, November 2010.
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Bibtex citation record
@InProceedings{Giachetti:2010:EAE, author = {Andrea Giachetti and {Jos{\'e} Antonio} {Iglesias Guiti{\'a}n} and Enrico Gobbetti}, title = {Edge adaptive and energy preserving volume upscaling for high quality volume rendering}, booktitle = {Eurographics Italian Chapter Conference}, pages = {17--23}, publisher = {Eurographics Association}, address = {Conference held in Genoa, Italy}, month = {November}, year = {2010}, abstract = { We describe an edge-directed optimization-based method for volumetric data supersampling. The method is based on voxel splitting and iterative refinement performed with a greedy optimization driven by the smoothing of second order gray level derivatives and the assumption that the average gray level in the original voxels region cannot change. Due to these assumptions, the method, which is the 3D extension of a recently proposed technique, is particularly suitable for upscaling medical imaging data creating physically reasonable voxel values and overcoming the so-called partial volume effect. The good quality of the results obtained is demonstrated through experimental tests. Furthermore, we show how offline 3D upscaling of volumes can be coupled with recent techniques to perform high quality volume rendering of large datasets, obtaining a better inspection of medical volumetric data. }, url = {http://vic.crs4.it/vic/cgi-bin/bib-page.cgi?id='Giachetti:2010:EAE'}, }
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